Abstract 641: VirMAP for cancer: Characterization of the intratumoral virome in virally-associated cancers and a resource for investigators
Authors: Yongwoo D. Seo, Neal Bhutiani, Matthew C. Wong, Ashish V. Damania, Golnaz Morad, Matthew Lastrapes, Alexander J. Lazar, Jennifer A. Wargo, Nadim J. Ajami
Journal: Cancer Research (2023)

Abstract Background: A major barrier to understanding the role of viruses in cancer progression has been the lack of sensitivity of current tools to identify and assemble viral genomes in an untargeted way. Here, we utilize our novel VirMAP algorithm to identify eukaryotic and prokaryotic viruses associated with cancers, using RNA sequencing data from The Cancer Genome Atlas (TCGA). Methods: VirMAP was used to analyze TCGA RNA-Seq data derived from primary tumor tissues, with a focus on cancers with known viral associations (cervical, ovarian, head and neck, liver, stomach and esophagus). Previously published survival data were matched with viral signatures for exploratory analysis. Ancom-BC, a differential abundance pipeline, was utilized to screen for viruses which drive outcome. Overall survival (OS) was assessed using the Kaplan-Meier method, and p-values were calculated using log-rank test. Multivariate analysis (MVA) was done using the Cox proportional hazards model to control for age, sex, stage, and histology. Results: Viral sequence recovery (among 723 billion sequencing reads from 2090 patients) was at least equal to previously published algorithms such as Kraken, but with higher taxonomic resolution. Cancers with high viral loads such as cervical cancer demonstrated high recovery rates (0.012% of all sequencing reads mapped to viral taxa, followed by 0.004% for liver, 0.0018% for head and neck squamous cell, 0.0016% for stomach, 0.0009% for esophageal, and 0.0002% for ovarian). There was a wide range of viral signature richness, with cervical cancer showing the highest viral read count predominated by HPV serotypes; in contrast, stomach cancer had lower abundance but contained over 300 unique viral taxa. Exploratory clinical analysis revealed novel correlations between viral signatures and OS. In cervical cancer, presence of HPV45 predicted worse survival (median OS 837 days vs 4086, p=0.0043); MVA demonstrated hazard ratio (HR) of 5.7 [2.6-11.4, p&amp;lt;0.0001]. In stomach cancer, patients often had more than one viral taxon present (mean 3.7, range 0-18); presence of 7 or more unique taxa predicted worse OS (median OS 403 days vs 1153, p=0.0001). MVA showed HR 1.1 for every additional taxon (p=0.0004). Conclusions: VirMAP performs deep characterization of the tumor-associated virome in both high and low abundance settings, with generation of partial genome reconstructions and strain level taxonomic classification. Utilizing publicly available platforms such as TCGA, clinical and correlative published data can be leveraged to better understand the nuanced pleotropic effects of the tumor virome on cancer progression. Citation Format: Yongwoo D. Seo, Neal Bhutiani, Matthew C. Wong, Ashish V. Damania, Golnaz Morad, Matthew Lastrapes, Alexander J. Lazar, Jennifer A. Wargo, Nadim J. Ajami. VirMAP for cancer: Characterization of the intratumoral virome in virally-associated cancers and a resource for investigators [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 641.